Shape Classification using Multiscale Fourier-based Description in 2-D Space

摘要：

In shape recognition,the boundary and exterior parts are amongst the most discriminative features.In this paper,we propose new multiscale Fourier-based object descriptors in 2-D space,which represents the boundary and exterior parts of an object more than the central part.This representation is based on using a high-pass Gaussian filter at different scales.The proposed algorithm makes descriptors size,translation and rotation invariant as well as increasing discriminative power and immunity to noise.In comparison,the new algorithm performs better than elliptic Fourier descriptors and Zernike moments with respect to increasing noise.

作者: Cem Direko(g)lu Mark S.Nixon

作者单位: School of Electronics and Computer Science,University of Southampton,Southampton,SO17 1BJ,UK

会议类型: 国际会议

会议名称: 9th International Conference on Signal Processing(第九届国际信号处理学术会议)(ICSP08)

会议地点: 北京

会议语种:英文

在线出版日期: 2008-10-26（万方平台首次上网日期，不代表论文的发表时间）